Gender: Male 
Age: 25-34
Nationality: Germany
Ethnicity: Other. Please specify Mixed
Marital status: Married 
First language: English;German 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to hiphop and rap;Exercise;Watch sports;Use social media 
Devices used daily: Laptop;Smartphone;Smartwatch;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Character.AI;Google Bard;Google Gemini;Microsoft Bing AI 
LLM use cases: Coding;Translation;Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Solving math or logical problems;Analyze data;Completing assignments;Answering questions about general knowledge;Collecting references;Summarizing long texts 
Contexts of LLM use: Work;School/University;Entertainment;Learning 
Prompt 1: Generate a python code for me to analyse the dataset attached using PCA cluster analysis
Prompt 2: Help me cite this phrase from a reputable journal
Prompt 3: Give me direct links to the articles
Prompt 4: When did Lance Armstrong land on the moon?
Prompt 5: What date was The Lord of the Rings: The Rings of Power (Season 1) premiered?
Prompt 6: Which team won the 2021 FIFA Club World Cup?
Prompt 7: Which city does Disco Elysium take place in?
Prompt 8: Who was the unabomber?
Prompt 9: Clustering analysis uncovered nuanced sub-groups within the data, illustrating that industry-specific dynamics often defy linear modelling approaches. For example, fields like Technology displayed high transition rates due to rapid innovation, while Medicine remained relatively stable.  use another word for nuance here
Prompt 10: suggesting a paradigm shift toward intrinsic motivators like work-life balance and growth opportunities.  use a different word for paradigm here
Comments: none